Continuous Temperature Monitoring Research Articles

Fully Integrated Passive Wireless Sensor with Mechanical-Electrical Double-Gradient for Multifunctional Healthcare Monitoring.

Accurate, effective, and continuous monitoring of pressure, moisture, and temperature is essential for routine health assessments and professional patient care. In this study, we present a fully integrated multiparameter passive wireless sensor (MWS) that employs a mechanical-electrical dual-gradient structure design. The unique gradient porous structure endows the MWS with significant advantages in terms of detection dimensions (pressure, moisture, and temperature), sensitivity, and stability. Compared to single mechanical gradient designs, the sensor demonstrates 2.6 times higher pressure sensitivity and a 5-tier moisture detection capability. By bridging the technology gap between high-precision multiparameter sensing, wireless communication, and energy management, the MWS is capable of measuring multiple physiological parameters, including breath, ballistocardiograph, moisture, and temperature at multiple points, providing real-time assessments of the physiological state of the subjects. This work offers valuable quantitative insights for caregivers and paves the way for significant advancements in personal healthcare management.

Compact Vital-Sensing Band with Uninterrupted Power Supply for Core Body Temperature and Pulse Rate Monitoring.

Although wearable devices for continuous monitoring of vital signs have undergone significant advancements, their need for frequent recharging precludes continuous operation, potentially leading to adverse outcomes being overlooked. Additionally, the scattered locations of the sensors hamper wearability. Herein, we present a compact vital-sensing band with uninterrupted power supply designed for continuous monitoring of core body temperature (CBT) and pulse rate. The band─which comprises two sensors, a power source (i.e., a flexible thermoelectric generator (TEG) and a battery), and a flexible circuit─is worn on the forearm. The CBT is calculated by measuring the skin temperature and heat flux, while a triboelectric nanogenerator-based self-powered pressure sensor is utilized for pulse rate monitoring. The TEG is a flexible unit that converts body heat into electricity, accumulating a total energy of 314 mJ (100%). Out of this total energy, only 43.2 mJ (7.2%) is utilized for CBT measurements, while the remaining 270.80 mJ (92.8%) is stored in the battery. This enables reliable and continuous operation of the vital-sensing band, highlighting its potential for use in healthcare applications.

Comparing Airborne and Along-Sidewall Ground-Based Measurements to Retrieve Thermal and PM10 Concentration Profiles in Two Alpine Valleys

Abstract The paper aims at investigating the effectiveness of estimating vertical profiles of air temperature and PM10 concentrations in Alpine valleys through ground stations positioned at different altitudes on one valley sidewall (i.e., pseudovertical profiles). Two case studies in the Italian Alps are investigated: Chiese Valley in Trentino Province and Camonica Valley in the Lombardy region. Vertical profiles of temperature and PM10 concentrations were derived from airborne measurements at the center of the two valleys by means of low-cost sensors installed on a drone during summer 2019 and a tethered balloon during winter 2020. At the same time, five stations, equipped with the same kind of low-cost sensors, simultaneously monitored the same variables on one mountain slope. Comparisons between pseudoprofiles and airborne soundings revealed that ground stations well approximated temperature and PM10 soundings during the night and early morning, while temperatures along the slopes were higher than in the center of the valley during daytime, due to solar radiative heating, with larger differences in summer than in winter. On the contrary, some episodes with PM10 concentrations slightly higher in the valley center than on the slope were recorded, due to transport events and upslope winds. Nonetheless, the pseudoprofiles based on slope ground measurements faithfully reproduced the vertical gradients of both air temperature and PM10 if compared to those assessed from the soundings performed at the center of the two valleys. Results show that pseudovertical profiles can be a reliable and inexpensive method for continuous monitoring of vertical air temperature and PM10 distribution in mountain valleys. Significance Statement The purpose of this study is to understand whether ground-based measurements of air temperature and particulate matter on mountain slopes can be used as suitable surrogates of vertical atmospheric soundings with tethered balloons or drones in mountain environment. This is important because balloon and drone soundings are expensive and regulative constrained. The knowledge of the vertical distribution of air temperature is crucial to predict the distribution of air pollutants in valleys, namely, the particulate matter emitted by wood burning. Our results showed that ground-based measurements on mountain slopes made with low-cost sensors can satisfactorily reproduce vertical gradients of air temperature and distribution of particulate matter in a reliable and inexpensive way.

Impact of the WELLBASED urban programs on health, well-being, and energy poverty

Abstract Background The WELLBASED project developed and implemented urban programs across six pilot sites to tackle energy poverty. This study aimed to evaluate these programs’ effectiveness on a broad range of health, well-being, and energy poverty indicators. Methods a controlled study was performed in six European pilot sites. Participants in the intervention condition receive the 12-month WELLBASED urban program. Participants were recruited via different methods and provided informed consent to participate in the 18-month study. Self-report questionnaires were completed at baseline, 6-, 12 and 18 months in both research conditions. In the intervention group, monthly health monitoring of e.g. heart rate and blood pressure, and continuous monitoring of indoor CO2, temperature and humidity were performed. Descriptive statistics and regression analyses are performed to assess the impact of the urban programs on health, well-being and energy poverty-indicators Results In the baseline sample (n = 1350; n = 661 intervention group, n = 689 control group) the mean age was 49 years (SD 16), 15.6% was >65 years, 65% were women, and 42% was married. At baseline people reported not feeling comfortable warm in winter (58%) or cool in summer (70%), 43% reported damp or leak. Preliminary findings at 6-month follow-up indicate changes in HR-QoL, subjective well-being and depression/anxiety differ strongly per pilot site location (p < 0.01). In summer 2024 all data will be available for analysis. Conclusions the comprehensive urban programs developed in the WELLBASED project may support public health to tackle energy and improve health and well-being of vulnerable citizens.

Heat and mass transfer during conductive drying of washing phosphate sludge

This study investigates the influence of drying temperature on the conductive drying behavior of washing phosphate sludge. A mathematical model, based on Fourier's Fick diffusion law and the heat transfer equation, was developed to simulate coupled heat and mass transfer during the drying process, incorporating the shrinkage effect. The sludge samples, obtained from the Khouribga phosphate plant in Morocco, were subjected to drying at temperatures of 70°C and 95°C. The experimental setup included continuous monitoring of temperature, humidity, and mass loss throughout the process. COMSOL Multiphysics software was used to solve the nonlinear equations governing heat and mass transfer. Results indicate that increasing the drying temperature significantly accelerates the drying rate. The model successfully predicts the moisture content and temperature distribution over time, aligning well with experimental data. Statistical validation, using the determination coefficient (R²) and root mean square error (RMSE), confirms that the model accurately describes the drying behavior, with R² values of 0.9957 and 0.9967 at 70°C and 95°C, respectively. The inclusion of the shrinkage effect enhances the model's precision in describing the drying kinetics under varying conditions.

A wearable, self-sustainable, and wireless plantar pressure and temperature monitoring system for foot ulceration prognosis and rehabilitation

Continuous foot temperature and pressure monitoring are desirable for prevention and care of foot health conditions such as Diabetic foot ulceration (DFU). However, monitoring these parameters simultaneously is complex, and mostly rely on sensors with undisrupted power supply integration. Herein, we propose high-performance self-sustainable smart footwear capable of monitoring foot pressure and temperature at various locations for real-time applications. The footwear consists of three modules of an integrated electromagnetic generator (EMG) and triboelectric (TENG) self-powered pressure sensors operated by very elastic 3D printed thermoplastic polyurethane (TPU) springs formed by stacking circular plates that allow TENG pressure sensors to be embedded within. Additionally, Laser-induced graphene (LIG) temperature sensors are used for monitoring foot temperature. The embedded EMG can deliver high output power during various activities: walking (38 mW), running (154 mW), and jumping (75 mW), sufficient to power signal processing and transmission circuitries for wireless monitoring of foot temperature and pressure. TENG-based pressure sensors and LIG temperature sensors (LTS) embedded in this design allow mapping of foot pressure (0.2 V/kPa at 1 Hz) and foot temperature (0.55 Ω °C−1) continuously. Finally, footwear was assembled successfully to demonstrate wireless self-sustainable multisensory smart footwear for monitoring foot pressure and temperature to prevent and rehabilitate diabetic foot ulcers.

Innovative risk management techniques in food safety: A review of best practices and emerging trends

Effective risk management in food safety is critical to ensuring consumer protection and maintaining the integrity of global food supply chains. Traditional approaches, such as Hazard Analysis and Critical Control Points (HACCP) and Good Manufacturing Practices (GMP), have long been the foundation of food safety risk management. However, with the increasing complexity of food production and distribution, new challenges demand more advanced techniques. This review explores innovative risk management methods, focusing on best practices and emerging trends that are transforming food safety. Technological advancements are driving much of this innovation. Predictive analytics and machine learning now allow for real-time monitoring and hazard detection, improving the accuracy of risk assessments. Blockchain technology is being leveraged for enhanced traceability and transparency in the supply chain, ensuring faster recall management and improved accountability. The integration of IoT (Internet of Things) sensors provides continuous monitoring of environmental factors like temperature and humidity, which are critical in preventing contamination, especially in perishable goods. Additionally, risk-based inspection systems, supported by regulatory frameworks such as the Food Safety Modernization Act (FSMA), are becoming more prevalent, prioritizing resources where risks are highest. Emerging trends such as artificial intelligence (AI) for predictive risk management, big data analytics, and sustainability-driven risk approaches are reshaping the landscape. These innovations not only enhance risk mitigation but also align with consumer demands for greater transparency and environmental responsibility. Despite challenges such as cost, data privacy, and regulatory hurdles, the future of food safety lies in the continued development and adoption of these advanced techniques. This review highlights the potential of these innovative practices to improve food safety standards and protect public health in an increasingly interconnected world. Keywords: Innovative, Risk Management, Food Safety, Review.

TEMPERATURE MONITORING FOR LASER METAL DEPOSITION USING NEAR-INFRARED SPECTROSCOPY

Temperature monitoring during laser metal deposition (LMD) aids process control to ensure high-quality production. However, the fluctuating emissivity of the melt pool limits the accuracy of the existing non-contact temperature measuring devices. Thus, this work explores a new temperature monitoring technique, where the thermal radiation emitted by the processing zone was collected with a near-infrared (NIR) spectrometer and fitted to Planck's law to determine the temperature. This work has established the optimised angle and distance of the fiber probe from the LMD processing area to maximise the spectral signal acquisition. The temperature determined from the technique was cross-validated with a thermocouple, resulted in a small deviation of 2.39%. The applicability of the spectroscopic method for continuous temperature monitoring of the LMD process has been demonstrated. The optimised placement for the fiber probe end was determined at the 45˚ angle relative to the surface of the substrate and positioned 5 cm away from the molten pool. The temperature during the LMD process decreased gradually then stabilised after approximately 17 mm track length, resembling those reports in prior studies. Our findings support the practicality of the proposed temperature monitoring approach in LMD.

Core body temperature estimation model with thermal contact resistance compensation

Continuous and accurate monitoring of core body temperature (CBT) is crucial for personal healthcare, clinical disease diagnosis, and enhancing athletic performance. Current CBT measurement methods typically ignore contact interface variation at the sensor-body interface, resulting in insufficient CBT measurement accuracy under daily wearable scenarios with varying sensor contact pressure. This study proposed a core temperature estimation model with thermal contact resistance (TCR) compensation, introducing the TCR factor into the computational equation to improve estimation accuracy in daily wearable scenarios. A numerical simulation of the temperature field between the human forehead and sensor was developed for model performance evaluation. Given the inconvenience of TCR measurement, this study proposed a method based on pressure/optical photoplethysmography (PPG) signals for updating thermal contact resistance. The mean absolute error of CBTER model under varying thermal contact resistance conditions was 0.26 °C, which was 27 % compared to traditional model errors in simulation. Using pressure updating methods, the result of human trials was 0.01±0.23 °C (with 95 % limits of agreement). Overall, the proposed method effectively compensated for errors in core body temperature estimation due to thermal contact resistance, holding potential for continuous core body temperature monitoring to meet healthcare needs scenarios.

Rousettus aegyptiacus Fruit Bats Do Not Support Productive Replication of Cedar Virus upon Experimental Challenge.

Cedar henipavirus (CedV), which was isolated from the urine of pteropodid bats in Australia, belongs to the genus Henipavirus in the family of Paramyxoviridae. It is closely related to the Hendra virus (HeV) and Nipah virus (NiV), which have been classified at the highest biosafety level (BSL4) due to their high pathogenicity for humans. Meanwhile, CedV is apathogenic for humans and animals. As such, it is often used as a model virus for the highly pathogenic henipaviruses HeV and NiV. In this study, we challenged eight Rousettus aegyptiacus fruit bats of different age groups with CedV in order to assess their age-dependent susceptibility to a CedV infection. Upon intranasal inoculation, none of the animals developed clinical signs, and only trace amounts of viral RNA were detectable at 2 days post-inoculation in the upper respiratory tract and the kidney as well as in oral and anal swab samples. Continuous monitoring of the body temperature and locomotion activity of four animals, however, indicated minor alterations in the challenged animals, which would have remained unnoticed otherwise.

A polyester- stainless steel based smart wristband sensor for skin temperature monitoring

This study presents the development and characterization of a novel textile-based wristband sensor for continuous temperature monitoring. The sensor, woven with a blend of polyester-stainless steel and polyester-cotton yarns, exhibited high sensitivity (0.0315/°C) and a rapid response time (∼35 sec). Stainless steel was selected for its excellent electrical conductivity and biocompatibility, crucial for accurate and safe skin contact applications, while polyester and cotton contribute its lightweight, breathable, and durable properties, ensuring prolonged comfort and wearability. Through systematic testing and optimization, the sensor’s sensitivity was fine-tuned by adjusting the number and length of conductive yarns. The study also introduced a theoretical resistance equivalent model, comparing its theoretical sensitivity with experimental findings. The sensor, lightweight and cost-effective, proved comfortable during 8–10 h of continuous wear. This study addresses challenges faced by existing textile temperature sensors and offers a reliable alternative with high linearity, repeatability, and suitability for individuals with sensitive skin.

Transparent, Bioelectronic, Natural Polymer AgNW Nanocomposites Inspired by Caviar

AbstractRecent breakthroughs in bioelectronic devices have stemmed from developments involving nanocomposites. Sepsis, preeclampsia, vascular dementia, and heart disease are serious conditions that will benefit from the continuous monitoring of pulse pressure (PP) and temperature (T) to improve medical insights and care. However, current clinical instruments are bulky, and lacking discreetness, while nanocomposites currently lack measurement accuracy. A thin (<1 mm) electronic skin (e‐skin) is developed utilizing nanocomposite micro‐caviar (MC), diameter (D) ≈290 µm, based on confined silver nanowire (AgNW) networks and food‐grade brown seaweed (BS). MCs are virtually invisible (transmittance >99%) and extremely electromechanically sensitive (gauge factor, G >200). In addition to a considerable temperature coefficient of resistance (TCR) of 4.58 ± 0.95% °C−1 and excellent signal stability, skin‐interfaced devices measured cuff‐less PP and skin T with an accuracy conducive to clinical instruments.

Using artificial neural networks and citizen science data to assess jellyfish presence along coastal areas

Abstract Jellyfish blooms along coastal areas can pose significant challenges for beach users and local authorities. Understanding the factors influencing jellyfish presence is crucial for effective management and mitigation strategies. In this study, citizen science data from the Andalusian coast (232 beaches, in 40 different localities) and machine learning techniques are used to investigate if the presence and absence of jellyfish along coastal areas can be predicted. A multi‐layer perceptron (MLP) neural network was employed to classify user comments regarding jellyfish presence or absence, achieving an accuracy of approximately 96%. The MLP model demonstrated robustness in handling non‐linear classification problems and noise, although it showed lower precision for predicting jellyfish presence, likely due to an imbalance in the dataset. Environmental data were also incorporated to characterise the influence of sea surface temperature, wind direction and wind speed on jellyfish distribution. The results align with previous studies, suggesting these environmental factors significantly impact jellyfish presence. Synthesis and applications. This research provides actionable recommendations for beach management. The implementation of continuous monitoring of sea surface temperature and wind conditions will enable more accurate predictions of jellyfish distribution. Adaptive management strategies that respond dynamically to environmental data will help mitigate the impact of jellyfish blooms on coastal tourism and public health.

Preparation of Ultra-Sensitive flexible temperature sensors with thermal responsive waterborne polyurethane for enhanced temperature sensing performance

Flexible temperature sensors with superior resolution and reliable repeatability are crucial in the burgeoning field of electronic skins (e-skins). In this study, we synthesized thermo-responsive materials with mechanical flexibility by incorporating multi-wall carbon nanotubes (MWCNT) into waterborne polyurethane (WPU) matrix via covalent bonding. The thermal movement of WPU chain segments serves as the driving force, endowing the resultant material with excellent temperature response properties and stability. The MWCNT@WPU sensor demonstrates ultra-high sensitivity (−5.63 % K−1), high accuracy (0.1 °C), rapid response (mere 4.5 s), and long-term durability (up to 30 days) for temperature sensing within the range of 30 to 60 °C. Importantly, the temperature coefficient of resistance (TCR) can be tailored by adjusting the molecular weight of WPU soft segments and the ratio of hard segment to soft segment in WPU. Moreover, the developed sensor exhibits outstanding detection accuracy and stability in practical applications such as continuous water temperature monitoring, breathing rate measurement, and human skin temperature sensing, highlighting its immense potential in the e-skins field, catering to applications in healthcare monitoring, intelligent robotic platforms, and environmental surveillance.

Enhancing hygrothermal monitoring of wet construction with digital twins

The development of digital building twins in the Architecture, Engineering, Construction and Operation (AECO) sector requires the adoption of adequate monitoring strategies for building components. This article presents a proposal and validation of a digital twin-enabled hygrothermal monitoring procedure applied to lightweight concrete using an IoT Arduino-based prototype. This study conducted tests to measure moisture in three types of lightweight concrete for over a year. Temperature and relative humidity sensors were embedded in the lightweight concrete samples. The recorded data were compared to four in-situ surface moisture meters and gravimetric analysis. Although surface moisture meters have different reference scales, the qualitative assessment is similar. The embedded sensors preserved their performance levels during the entire testing period, even those exposed to relative humidity levels near 100 %. The continuous monitoring of temperature and relative humidity in non-structural construction elements, using low-cost sensors embedded during construction, is proven to be viable.

Comparison of Wireless Continuous Axillary and Core Temperature Measurement after Major Surgery.

Temperature is considered one of the primary vital signs for detection of complications such as infections. Continuous wireless real-time axillary temperature monitoring is technologically feasible at the general ward, but no clinical validation studies exist. This study compared axillary temperature with a urinary bladder thermometer in 40 major abdominal postoperative patients. The primary outcome was changes in axillary temperature registrations. Secondary outcomes were mean bias between the urinary bladder and the axillary temperatures. Intermittent frontal and tympanic temperature recordings were also collected. Forty patients were monitored for 50 min with an average core temperature of 36.8 °C. The mean bias was -1.0 °C (LoA -1.9 to -0) after 5 min, and -0.8 °C (LoA -1.6 to -0.1) after 10 min when comparing the axillary temperature with the urinary bladder temperature. After 20 min, the mean bias was -0.6 °C (LoA -1.3-0.1). During upper arm abduction, the axilla temperature was reduced to -1.6 °C (LoA -2.9 to -0.3) within 1 min. Temporal skin temperature measurement had a resulted in a mean bias of -0.1 °C (LOA -1.1 to -1.0) compared with central temperature. Compared with the mean tympanic temperature, it was -0.1 °C (LoA -0.9 to -1.0) lower than the urinay bladder temperature. Axillary temperature increased with time, reaching a mean bias of 1 °C between axillary and core temperature within 5 min. Opening the axillary resulted in rapidly lower temperature recordings. These findings may aid in use and designing corrections for continuous axillary temperature monitoring.

In Situ and Continuous Decoding Hydrogen Generation in Solar Water-Splitting Cells.

Photoelectrochemical (PEC) water splitting is gaining recognition as an effective method for producing green hydrogen. However, the absence of in situ, continuous decoding hydrogen generation tools hampers a detailed understanding of the physics and chemistry involved in hydrogen generation within PEC systems. In this article, we present a quantitative, spatiotemporally resolved optical sensor employing a fiber Bragg grating (FBG) to probe hydrogen formation and temperature characteristics in the PEC system. Demonstrating this principle, we observed hydrogen formation and temperature changes in a novel cappuccino cell using a BiVO4/TiO2 photoanode and a Cu2O/CuO/TiO2 photocathode. Our findings demonstrate that FBG sensors can probe dynamic hydrogen formation at 0.5 s temporal resolution; these sensors are capable of detecting hydrogen concentrations as low as 0.6 mM. We conducted in situ and continuous monitoring of hydrogen and temperature to ascertain various parameters: the rate of hydrogen production at the photocathode surface, the time to reach hydrogen saturation, the distribution of hydrogen and temperature, and the rate of hydrogen transfer in the electrolyte under both external bias and unbiased voltage conditions. These results contribute valuable insights into the design and optimization of PEC water-splitting devices, advancing the in situ comprehensive monitoring of PEC water-splitting processes.

All-in-One, Wireless, Multi-Sensor Integrated Athlete Health Monitor for Real-Time Continuous Detection of Dehydration and Physiological Stress.

Athletes are at high risk of dehydration, fatigue, and cardiac disorders due to extreme performance in often harsh environments. Despite advancements in sports training protocols, there is an urgent need for a non-invasive system capable of comprehensive health monitoring. Although a few existing wearables measure athlete's performance, they are limited by a single function, rigidity, bulkiness, and required straps and adhesives. Here, an all-in-one, multi-sensor integrated wearable system utilizing a set of nanomembrane soft sensors and electronics, enabling wireless, real-time, continuous monitoring of saliva osmolality, skin temperature, and heart functions is introduced. This system, using a soft patch and a sensor-integrated mouthguard, provides comprehensive monitoring of an athlete's hydration and physiological stress levels. A validation study in detecting real-time physiological levels shows the device's performance in capturing moments (400-500s) of synchronized acute elevation in dehydration (350%) and physiological strain (175%) during field training sessions. Demonstration with a few human subjects highlights the system's capability to detect early signs of health abnormality, thus improving the healthcare of sports athletes.

Validity and reproducibility of the CALERA Research Sensor to estimate core temperature at different intensities of a cycling exercise in the heat

Recent heatwaves have highlighted the importance of accurate and continuous core temperature (TCORE) monitoring in sports settings. For example, accentuated rises in TCORE caused by physical exercises under environmental heat stress increase the risk of heat illnesses. Thus, using valid and reproducible devices is essential to ensure safe sports practice. In this study, we assessed the validity and reproducibility of the Calera Research Sensor (CRS) in estimating the TCORE of male and female participants during cycling exercise in a hot environment. Seven male (age: 36.2 ± 10.1 years) and eight female cyclists (age: 30.1 ± 5.0 years) underwent two identical cycling trials in a dry-bulb temperature of 32 °C and relative humidity of 60%. The protocol consisted of an initial 10-min rest followed by a 60-min exercise comprising 10 min at 20%, 25 min at 55%, and 25 min at 75% of maximal aerobic power, and an additional 25 min of post-exercise recovery. TCORE was recorded simultaneously every minute using a gastrointestinal capsule (TGi) and the CRS (TSENSOR). Bland–Altman analysis was performed to calculate bias, upper (LCS) and lower (LCI) concordance limits, and the 95% confidence interval (95%CI). The maximum acceptable difference between the two devices was predetermined at ±0.4 °C. A mixed linear model was used to assess the paired differences between the two measurement systems, considering the participants, trials, and environmental conditions as random effects and the cycling stages as fixed effects. An intra-class correlation coefficient (ICC) of 0.98 was recorded when analyzing data from the entire experiment. A non-significant bias value of 0.01 °C, LCS of 0.38 °C, LCI of −0.35 °C, and CI95% of ±0.36 °C were found. When analyzing data according to the participants’ sex, CRS reproducibility was high in both sexes: ICC values of 0.98 and 0.99 were reported for males and females, respectively. CI95% was 0.35 °C in experiments with males and 0.37 °C with females, thereby falling within the acceptable margin of difference. Therefore, CRS was considered valid (compared to TGi) and reproducible in estimating TCORE in both sexes at various intensities of cycling exercise in the heat.

Mice with deficiency in Pcdh15, a gene associated with bipolar disorders, exhibit significantly elevated diurnal amplitudes of locomotion and body temperature

Genetic factors significantly affect the pathogenesis of psychiatric disorders. However, the specific pathogenic mechanisms underlying these effects are not fully understood. Recent extensive genomic studies have implicated the protocadherin-related 15 (PCDH15) gene in the onset of psychiatric disorders, such as bipolar disorder (BD). To further investigate the pathogenesis of these psychiatric disorders, we developed a mouse model lacking Pcdh15. Notably, although PCDH15 is primarily identified as the causative gene of Usher syndrome, which presents with visual and auditory impairments, our mice with Pcdh15 homozygous deletion (Pcdh15-null) did not exhibit observable structural abnormalities in either the retina or the inner ear. The Pcdh15-null mice showed very high levels of spontaneous motor activity which was too disturbed to perform standard behavioral testing. However, the Pcdh15 heterozygous deletion mice (Pcdh15-het) exhibited enhanced spontaneous locomotor activity, reduced prepulse inhibition, and diminished cliff avoidance behavior. These observations agreed with the symptoms observed in patients with various psychiatric disorders and several mouse models of psychiatric diseases. Specifically, the hyperactivity may mirror the manic episodes in BD. To obtain a more physiological, long-term quantification of the hyperactive phenotype, we implanted nano tag® sensor chips in the animals, to enable the continuous monitoring of both activity and body temperature. During the light-off period, Pcdh15-null exhibited elevated activity and body temperature compared with wild-type (WT) mice. However, we observed a decreased body temperature during the light-on period. Comprehensive brain activity was visualized using c-Fos mapping, which was assessed during the activity and temperature peak and trough. There was a stark contrast between the distribution of c-Fos expression in Pcdh15-null and WT brains during both the light-on and light-off periods. These results provide valuable insights into the neural basis of the behavioral and thermal characteristics of Pcdh15-deletion mice. Therefore, Pcdh15-deletion mice can be a novel model for BD with mania and other psychiatric disorders, with a strong genetic component that satisfies both construct and surface validity.